SPONSORED CONTENT LABORATORY INFORMATICS


the events and processes leading to them.’


It is a complex challenge and many


organisations are only just now realising the potential to use the tools that are available to them. Capturing data in a structured and standardised way in a centralised location, is what allows organisations to start deriving actionable insights from that data. There is little point in capturing all this data if you don’t do that hard work to capture it in a way that is usable. Laboratory information management


systems (LIMS) and electronic laboratory notebooks (ELN) software can provide a good starting point for data management, but this depends on the workloads and applications that are being used in a specific laboratory. In some cases, LIMS and ELN software


will require additional integration with other software tools for analysis, library or registration of molecular data which can create additional steps in ensuring data is consistent. Consolidating and bringing data into a


centralised LIMS system can help improve data quality and integrity but is likely to have inconsistencies and duplicates, which requires manual data cleansing.


For scientists working with pharmaceutical or biotechnology data such as sequencing results, fermentation results, omics data and other associated metadata, this challenge can be particularly acute. For laboratories engaged in these disciplines, a single platform that can handle experimental results, associated metadata, sequencing and design tools could be the answer. While legacy software is built according


to outdated, potentially inaccurate notions of how scientists and organisations work, modern software tools for laboratory scientists need to reflect how scientists work today. Benchling provides laboratory


notebook alongside analysis tools for molecular biology, inventory management and registry functionality into a single platform to centralise biotechnology data. This enables scientists to access data either in cloud-based software tools for digital DNA sequence editing, designing and running experiments, analysing data, and sharing research. James Broughton, research lead at Mammoth Biosciences, said: ‘Our Crispr-enabled platform for disease detection and bio-sensing grapples with the tremendous complexity of biological


systems. Thanks to the scalability of the cloud, we can now explore massive amounts of DNA data and foster important innovations that promise to transform a range of industries – from healthcare to agriculture and beyond.’ Arsenal Bio’s CSO and scientific co-


founder Dr Theo Roth, said: ‘At ArsenalBio, we’re building the next generation of programmable cell therapies to bring these curative treatments to many more patients. ‘This involves extensive novel DNA design and construction work, and Benchling has created ideal tools for our teams to collaboratively complete these complex molecular projects. ‘It has accelerated the development of our gene-editing technologies and the synthetic DNA sequences that will power the next generation of cellular therapies,’ he said. For modern biotechnology workflows,


controlling and managing the creation of data so that it can be effectively reused and shared is crucial to maintaining productivity and increasing efficiency. Utilising modern laboratory tools can expedite this process, enabling organisations to get ahead of the curve and manage data effectively.


New White paper now online


The R&D Data Maturity Curve (Benchling)


The volume and complexity of life science R&D data has exploded. To be successful R&D organizations must harness the full power of their data to drive faster, smarter decision making. Learn how to take your R&D data to the next level with this step-by-step guide from Benchling.


www.scientific-computing.com/white-papers


SCIENTIFIC COMPUTING WORLD


www.scientific-computing.com | @scwmagazine Autumn 2020 Scientific Computing World 29


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